Kanser Araştırmalarında Laboratuvar Hayvanı Modellerinde Geleneksel Yaklaşımlar ve Yenilikçi Stratejiler: Kapsamlı Bir İnceleme

Yıl 2024, Cilt: 26 Sayı: S1, 36 - 46, 30.06.2024

Mümin Alper Erdoğan

https://doi.org/10.18678/dtfd.1496879

Öz

Kanser, tıbbi araştırmalarda önemli bir zorluk olarak kalmaya devam etmektedir ve karmaşıklığını anlamak ve etkili tedaviler geliştirmek için çeşitli ve karmaşık modellere ihtiyaç duyulmaktadır. Bu derlemenin amacı, deneysel kanser modellerinin evrimini ve faydasını incelemek ve temel araştırma ile klinik uygulama arasındaki boşluğu kapatmada önemli rol oynadıklarını vurgulamaktır. Tümör büyümesini ve ilaç yanıtını bir canlı organizmada çalışmak için doğrudan bir yol sağlayan ksenograftların geleneksel kullanımından, insan kanserinin genetik ve fenotipik özelliklerini kopyalayan genetiği değiştirilmiş fare modellerinin (genetically engineered mouse models, GEMMs) yenilikçi yaklaşımlarına kadar, her model kanser biyolojisine benzersiz bir bakış sunmaktadır. Son dönemdeki ilerlemeler, tümörün mikroçevresini yakından taklit eden üç boyutlu bir perspektif sunan organoid modellerini ve hastalık ilerlemesini ve tedavi sonuçlarını tahmin etmek için hastaya özgü verileri kullanan hesaplama modellerini tanıtmıştır. Bu modeller, kanserin moleküler etkenlerinin anlaşılmasına yardımcı olmakta, hedefe yönelik tedavilerin geliştirilmesini kolaylaştırmakta ve onkolojide kişiselleştirilmiş tıbbın önemini vurgulamaktadır. Bu deneysel modellerin çeşitliliği ve potansiyeline rağmen, tümörün karmaşıklığının kopyalanması ve bağışıklık sistemi etkileşimlerinin entegrasyonu gibi zorluklar devam etmektedir. Gelecekteki araştırmalar, tahmin doğruluklarının artırılmasına ve güçlü yanlarının birleştirilmesine odaklanarak kanser biyolojisi ve tedavisine bütünsel bir bakış açısı sunmak için bu modellerin iyileştirilmesine yöneliktir.

Anahtar Kelimeler

Kanser deneysel araştırma, ksenograft, genetiği değiştirilmiş fare modelleri, organoid model, hesaplamalı modeller, kişiselleştirilmiş tıp, tümör mikroçevre

Traditional Approaches and Innovative Strategies in Laboratory Animal Models for Cancer Research: A Comprehensive Review

Öz

Cancer remains one of the foremost challenges in medical research, necessitating diverse and sophisticated models to understand its complexity and develop effective treatments. This review explores the evolution and utility of experimental cancer models, highlighting their pivotal role in bridging the gap between basic research and clinical application. From the traditional use of xenografts, which provide a direct avenue for studying tumor growth and drug response in a living organism, to the innovative approaches of genetically engineered mouse models (GEMMs) that replicate human cancer's genetic and phenotypic traits, each model offers unique insights into cancer biology. Recent advances have introduced organoid models, offering a three-dimensional perspective that closely mimics the tumor's microenvironment, and computational models, which leverage patient-specific data to predict disease progression and treatment outcomes. These models enhance our understanding of cancer's molecular drivers, facilitate the development of targeted therapies, and underscore the importance of personalized medicine in oncology. Despite the diversity and potential of these experimental models, challenges remain, including the replication of the tumor's complexity and the integration of immune system interactions. Future research is directed toward refining these models, improving their predictive accuracy, and combining their strengths to offer a holistic view of cancer biology and treatment.

Anahtar Kelimeler

Cancer experimental research, xenograft, genetically engineered mouse models, organoid model, computational models, personalized medicine, tumor microenvironment

Kaynakça

• Loeuillard E, Fischbach SR, Gores GJ, Ilyas SI. Animal models of cholangiocarcinoma. Biochim Biophys Acta Mol Basis Dis. 2019;1865(5):982-92.
• Kwon MC, Berns A. Mouse models for lung cancer. Mol Oncol. 2013;7(2):165-77.
• Gremonprez F, Willaert W, Ceelen W. Animal models of colorectal peritoneal metastasis. Pleura Peritoneum. 2016;1(1):23-43.
• Fichtner I, Rolff J, Soong R, Hoffmann J, Hammer S, Sommer A, et al. Establishment of patient derived non-small cell lung cancer xenografts as models for the identification of predictive biomarkers. Clin Cancer Res. 2008;14(20):6456-68.
• Hodgkinson CL, Morrow CJ, Li Y, Metcalf RL, Rothwell DG, Trapani F, et al. Tumorigenicity and genetic profiling of circulating tumor cells in small-cell lung cancer. Nat Med. 2014;20(8):897-903.
• Walrath JC, Hawes JJ, Van Dyke T, Reilly KM. Genetically engineered mouse models in cancer research. Adv Cancer Res. 2010;106:113-64.
• Ittmann M, Huang J, Radaelli E, Martin P, Signoretti S, Sullivan R, et al. Animal models of human prostate cancer: the consensus report of the New York meeting of the Mouse Models of Human Cancers Consortium Prostate Pathology Committee. Cancer Res. 2013;73(9):2718-36.
• Kemp CJ. Animal models of chemical carcinogenesis: driving breakthroughs in cancer research for 100 years. Cold Spring Harb Protoc. 2015;2015(10):865-74.
• Almosailleakh M, Schwaller J. Murine models of acute myeloid leukaemia. Int J Mol Sci. 2019;20(2):453.
• Rein A. Murine leukemia viruses: objects and organisms. Adv Virol. 2011;2011:403419.
• Kellar A, Egan C, Morris D. Preclinical murine models for lung cancer: clinical trial applications. Biomed Res Int. 2015;2015:621324.
• Üstüner C, Entok E. Experimental animal models for lung cancer. Nucl Med Semin. 2019;5(1):40-8.
• Jin Y, Liu M, Sa R, Fu H, Cheng L, Chen L. Mouse models of thyroid cancer: Bridging pathogenesis and novel therapeutics. Cancer Lett. 2020;469:35-53.
• Zhang L, Gaskins K, Yu Z, Xiong Y, Merino MJ, Kebebew E. An in vivo mouse model of metastatic human thyroid cancer. Thyroid. 2014;24(4):695-704.
• Hiroshima Y, Maawy A, Zhang Y, Zhang N, Murakami T, Chishima T, et al. Patient-derived mouse models of cancer need to be orthotopic in order to evaluate targeted anti-metastatic therapy. Oncotarget. 2016;7(44):71696-702.
• Xing M, Alzahrani AS, Carson KA, Viola D, Elisei R, Bendlova B, et al. Association between BRAF V600E mutation and mortality in patients with papillary thyroid cancer. JAMA. 2013;309(14):1493-501.
• Cho JY, Sagartz JE, Capen CC, Mazzaferri EL, Jhiang SM. Early cellular abnormalities induced by RET/PTC1 oncogene in thyroid-targeted transgenic mice. Oncogene. 1999;18(24):3659-65.
• Powell DJ Jr, Russell JP, Li G, Kuo BA, Fidanza V, Huebner K, et al. Altered gene expression in immunogenic poorly differentiated thyroid carcinomas from RET/PTC3p53-/- mice. Oncogene. 2001;20(25):3235-46.
• Miller KA, Yeager N, Baker K, Liao XH, Refetoff S, Di Cristofano A. Oncogenic Kras requires simultaneous PI3K signaling to induce ERK activation and transform thyroid epithelial cells in vivo. Cancer Res. 2009;69(8):3689-94.
• Kirschner LS, Qamri Z, Kari S, Ashtekar A. Mouse models of thyroid cancer: A 2015 update. Mol Cell Endocrinol. 2016;421:18-27.
• Pozo K, Castro-Rivera E, Tan C, Plattner F, Schwach G, Siegl V, et al. The role of Cdk5 in neuroendocrine thyroid cancer. Cancer Cell. 2013;24(4):499-511.
• Antico Arciuch VG, Russo MA, Dima M, Kang KS, Dasrath F, Liao XH, et al. Thyrocyte-specific inactivation of p53 and Pten results in anaplastic thyroid carcinomas faithfully recapitulating human tumors. Oncotarget. 2011;2(12):1109-26.
• Tsubura A, Lai YC, Miki H, Sasaki T, Uehara N, Yuri T, et al. Review: Animal models of N-methyl-N-nitrosourea-induced mammary cancer and retinal degeneration with special emphasis on therapeutic trials. In Vivo. 2011;25(1):11-22.
• Bazm MA, Naseri L, Khazaei M. Methods of inducing breast cancer in animal models: a systematic review. World Cancer Res J. 2018;5(4):e1182.
• Sydnor KL, Cockrell B. Influence of estradiol-17-beta, progesterone and hydrocortisone on 3-methylcholanthrene-induced mammary cancer in intact and ovariectomized Sprague-Dawley rats. Endocrinology.1963;73:427-32.
• Lai H, Singh NP. Oral artemisinin prevents and delays the development of 7,12-dimethylbenz[a]anthracene (DMBA)-induced breast cancer in the rat. Cancer Lett. 2006;231(1):43-8.
• Gao ZG, Tian L, Hu J, Park IS, Bae YH. Prevention of metastasis in a 4T1 murine breast cancer model by doxorubicin carried by folate conjugated pH sensitive polymeric micelles. J Control Release. 2011;152(1):84-9.
• Calaf GM, Hei TK. Establishment of a radiation-and estrogen-induced breast cancer model. Carcinogenesis. 2000;21(4):769-76.
• Vesselinovitch SD, Koka M, Mihailovich N, Rao KV. Carcinogenicity of diethylnitrosamine in newborn, infant, and adult mice. J Cancer Res Clin Oncol. 1984;108(1):60-5.
• Zhang HE, Henderson JM, Gorrell MD. Animal models for hepatocellular carcinoma. Biochim Biophys Acta Mol Basis Dis. 2019;1865(5):993-1002.
• Kisseleva T, Cong M, Paik Y, Scholten D, Jiang C, Benner C, et al. Myofibroblasts revert to an inactive phenotype during regression of liver fibrosis. Proc Natl Acad Sci U S A. 2012;109(24):9448-53.
• Zaldivar MM, Pauels K, von Hundelshausen P, Berres ML, Schmitz P, Bornemann J, et al. CXC chemokine ligand 4 (Cxcl4) is a platelet-derived mediator of experimental liver fibrosis. Hepatology. 2010;51(4):1345-53.
• Salguero Palacios R, Roderfeld M, Hemmann S, Rath T, Atanasova S, Tschuschner A, et al. Activation of hepatic stellate cells is associated with cytokine expression in thioacetamide-induced hepatic fibrosis in mice. Lab Invest. 2008;88(11):1192-203.
• Yang MH, Chen WJ, Fu YS, Huang B, Tsai WC, Arthur Chen YM, et al. Utilizing glycine N-methyltransferasegene knockout mice as a model for identification of missing proteins in hepatocellular carcinoma. Oncotarget. 2017;9(1):442-52.
• Thamavit W, Pairojkul C, Tiwawech D, Itoh M, Shirai T, Ito N. Promotion of cholangiocarcinogenesis in the hamster liver by bile duct ligation after dimethylnitrosamine initiation. Carcinogenesis. 1993;14(11):2415-7.
• Praet MM, Roels HJ. Histogenesis of cholangiomas and cholangiocarcinomas in thioacetamide fed rats. Exp Pathol. 1984;26(1):3-14.
• Maronpot RR, Giles HD, Dykes DJ, Irwin RD. Furan-induced hepatic cholangiocarcinomas in Fischer 344 rats. Toxicol Pathol. 1991;19(4 Pt 2):561-70.
• Tatematsu M, Yamamoto M, Shimizu N, Yoshikawa A, Fukami H, Kaminishi M, et al. Induction of glandular stomach cancers in Helicobacter pylori-sensitive Mongolian gerbils treated with N-methyl-N-nitrosourea and N-methyl-N’-nitro-N-nitrosoguanidine in drinking water. Jpn J Cancer Res. 1998;89(2):97-104.
• Hayakawa Y, Fox JG, Gonda T, Worthley DL, Muthupalani S, Wang TC. Mouse models of gastric cancer. Cancers (Basel). 2013;5(1):92-130.
• Poh AR, O’Donoghue RJ, Ernst M, Putoczki TL. Mouse models for gastric cancer: Matching models to biological questions. J Gastroenterol Hepatol. 2016;31(7):1257-72.
• Lefebvre O, Chenard MP, Masson R, Linares J, Dierich A, LeMeur M, et al. Gastric mucosa abnormalities and tumorigenesis in mice lacking the pS2 trefoil protein. Science. 1996;274(5285):259-62.
• Bobek P, Galbavy S, Ozdin L. Effect of oyster mushroom (Pleurotus ostreatus) on pathological changes in dimethylhydrazine-induced rat colon cancer. Oncol Rep. 1998;5(3):727-30.
• Mittal VK, Bhullar JS, Jayant K. Animal models of human colorectal cancer: Current status, uses and limitations. World J Gastroenterol. 2015;21(41):11854-61.
• Kishimoto H, Momiyama M, Aki R, Kimura H, Suetsugu A, Bouvet M, et al. Development of a clinically-precise mouse model of rectal cancer. PLoS One. 2013;8(11):e79453.
• Zigmond E, Halpern Z, Elinav E, Brazowski E, Jung S, Varol C. Utilization of murine colonoscopy for orthotopic implantation of colorectal cancer. PLoS One. 2011;6(12):e28858.
• DE-Souza ASC, Costa-Casagrande TA. Animal models for colorectal cancer. Arq Bras Cir Dig. 2018;31(2):e1369.
• Yamada Y, Mori H. Multistep carcinogenesis of the colon in Apc(Min/+) mouse. Cancer Sci. 2007;98(1):6-10.
• Sakai H, Tsukamoto T, Yamamoto M, Shirai N, Iidaka T, Hirata A, et al. High susceptibility of nullizygous p53 knockout mice to colorectal tumor induction by 1,2-dimethylhydrazine. J Cancer Res Clin Oncol. 2003;129(6):335-40.
• Fidler IJ. The pathogenesis of cancer metastasis: the 'seed and soil' hypothesis revisited. Nat Rev Cancer. 2003;3(6):453-8.
• Nguyen DX, Bos PD, Massagué J. Metastasis: from dissemination to organ-specific colonization. Nat Rev Cancer. 2009;9(4):274-84.
• Weiss L. Metastatic inefficiency. Adv Cancer Res. 1990;54:159-211.
• Vandamme TF. Use of rodents as models of human diseases. J Pharm Bioallied Sci. 2014;6(1):2-9.
• Tentler JJ, Tan AC, Weekes CD, Jimeno A, Leong S, Pitts TM, et al. Patient-derived tumour xenografts as models for oncology drug development. Nat Rev Clin Oncol. 2012;9(6):338-50.
• Kopetz S, Lemos R, Powis G. The promise of patient-derived xenografts: the best laid plans of mice and men. Clin Cancer Res. 2012;18(19):5160-2.
• Jin K, Teng L, Shen Y, He K, Xu Z, Li G. Patient-derived human tumour tissue xenografts in immunodeficient mice: a systematic review. Clin Transl Oncol. 2010;12(7):473-80.
• Shimosato Y, Kameya T, Nagai K, Hirohashi S, Koide T, Hayashi H, et al. Transplantation of human tumors in nude mice. J Natl Cancer Inst. 1976;56(6):1251-60.
• Cutz JC, Guan J, Bayani J, Yoshimoto M, Xue H, Sutcliffe M, et al. Establishment in severe combined immunodeficiency mice of subrenal capsule xenografts and transplantable tumor lines from a variety of primary human lung cancers: potential models for studying tumor progression-related changes. Clin Cancer Res. 2006;12(13):4043-54.
• Wettersten HI, Ganti S, Weiss RH. Metabolomic profiling of tumor-bearing mice. Methods Enzymol. 2014;543:275-96.
• Hidalgo M, Amant F, Biankin AV, Budinská E, Byrne AT, Caldas C, et al. Patient-derived xenograft models: an emerging platform for translational cancer research. Cancer Discov. 2014;4(9):998-1013.
• Dobrolecki LE, Airhart SD, Alferez DG, Aparicio S, Behbod F, Bentires-Alj M, et al. Patient-derived xenograft (PDX) models in basic and translational breast cancer research. Cancer Metastasis Rev. 2016;35(4):547-73.
• Pillai SPS, Uthamanthil RK. PDX models: history and development. In: Uthamanthil R, Tinkey P, editors. Patient derived tumor xenograft models: promise, potential and practice. London: Elsevier; 2017. p.1-12.
• Abate-Shen C, Brown PH, Colburn NH, Gerner EW, Green JE, Lipkin M, et al. The untapped potential of genetically engineered mouse models in chemoprevention research: opportunities and challenges. Cancer Prev Res (Phila). 2008;1(3):161-6.
• Green JE, Hudson T. The promise of genetically engineered mice for cancer prevention studies. Nat Rev Cancer. 2005;5(3):184-98.
• Brandon-Warner E, Schrum LW, Schmidt CM, McKillop IH. Rodent models of alcoholic liver disease: of mice and men. Alcohol. 2012;46(8):715-25.
• Hanahan D, Wagner EF, Palmiter RD. The origins of oncomice: a history of the first transgenic mice genetically engineered to develop cancer. Genes Dev. 2007;21(18):2258-70.
• Van Dyke T, Jacks T. Cancer modeling in the modern era: progress and challenges. Cell. 2002;108(2):135-44.
• Frese KK, Tuveson DA. Maximizing mouse cancer models. Nat Rev Cancer. 2007;7(9):654-58.
• Olive KP, Tuveson DA. The use of targeted mouse models for preclinical testing of novel cancer therapeutics. Clin Cancer Res. 2006;12(18):5277-87.
• Porru M, Leonetti C. The role of mouse models in translational cancer research: present and future directions. Transl Med Rep. 2020;4(1):64-9.
• Brown ZJ, Heinrich B, Greten TF. Mouse models of hepatocellular carcinoma: an overview and highlights for immunotherapy research. Nat Rev Gastroenterol Hepatol. 2018;15(9):536-54.
• Voskoglou-Nomikos T, Pater JL, Seymour L. Clinical predictive value of the in vitro cell line, human xenograft, and mouse allograft preclinical cancer models. Clin Cancer Res. 2003;9(11):4227-39.
• Sachs N, Clevers H. Organoid cultures for the analysis of cancer phenotypes. Curr Opin Genet Dev. 2014;24:68-73.
• Huch M, Knoblich JA, Lutolf MP, Martinez-Arias A. The hope and the hype of organoid research. Development. 2017;144(6):938-41.
• Yang H, Sun L, Liu M, Mao Y. Patient-derived organoids: a promising model for personalized cancer treatment. Gastroenterol Rep (Oxf). 2018;6(4):243-5.
• Tuveson D, Clevers H. Cancer modeling meets human organoid technology. Science. 2019;364(6444):952-5.
• Kim J, Koo BK, Knoblich JA. Human organoids: model systems for human biology and medicine. Nat Rev Mol Cell Biol.2020;21(10):571-84.
• Lo YH, Karlsson K, Kuo CJ. Applications of organoids for cancer biology and precision medicine. Nat Cancer. 2020;1(8):761-73.
• Pauli C, Hopkins BD, Prandi D, Shaw R, Fedrizzi T, Sboner A, et al. Personalized in vitro and in vivo cancer models to guide precision medicine. Cancer Discov. 2017;7(5):462-77.
• Savoia C, Volpe M, Grassi G, Borghi C, Agabiti Rosei E, Touyz RM. Personalized medicine-a modern approach for the diagnosis and management of hypertension. Clin Sci (Lond). 2017;131(22):2671-85.
• Barbolosi D, Ciccolini J, Lacarelle B, Barlési F, André N. Computational oncology--mathematical modelling of drug regimens for precision medicine. Nat Rev Clin Oncol. 2016;13(4):242-54.
• Morgan MM, Johnson BP, Livingston MK, Schuler LA, Alarid ET, Sung KE, et al. Personalized in vitro cancer models to predict therapeutic response: challenges and a framework for improvement. Pharmacol Ther. 2016;165:79-92.
• Wierling C, Kessler T, Ogilvie LA, Lange BM, Yaspo ML, Lehrach H. Network and systems biology: essential steps in virtualising drug discovery and development. Drug Discov Today Technol. 2015;15:33-40.
• Ogilvie LA, Kovachev A, Wierling C, Lange BMH, Lehrach H. Models of models: a translational route for cancer treatment and drug development. Front Oncol. 2017;7:219.
• Jean-Quartier C, Jeanquartier F, Jurisica I, Holzinger A. In silico cancer research towards 3R. BMC Cancer. 2018;18(1):408.
• Jones W, Alasoo K, Fishman D, Parts L. Computational biology: deep learning. Emerging Top Life Sci. 2017;1(3):257-74.